Identification of financial statement fraud in Greece by using computational intelligence techniques

The consequences of financial fraud are an issue with far-reaching for investors, lenders, regulators, corporate sectors and consumers. The range of development of new technologies such as cloud and mobile computing in recent years has compounded the problem. Manual detection which is a traditional method is not only inaccurate, expensive and time-consuming but also they are impractical for the management of big data. Auditors, financial institutions and regulators have tried to automated processes using statistical and computational methods. This paper presents comprehensive research in financial statement fraud detection by using machine learning techniques with a particular focus on computational intelligence (CI) techniques. We have collected a sample of 2469 observations since 2002 to 2015. Research gap was identified as none of the existing researchers address the association between financial statement fraud and CI-based detection algorithms and their performance, as reported in the literature. Also, the innovation of this research is that the selection of data sample is aimed to create models which will be capable of detecting the falsification in financial statements

Euro and Profitability of Greek Banks

The Greek Banking System, in its effort to prepare itself for the changeover to the EURO, will face some initial costs. Being the basic institution of money distribution, this changeover will impose a heavy burden on banks. In addition to the costs that banks will sustain, they will derive new benefits. The impact of the EURO on Greek Banks is explained through a cost-benefit analysis, by providing a perspective of the anticipated costs, benefits and outcome. The primary objective of this paper is to examine the costs that will arise from this changeover and the benefits that will be produced, as explained by the change in the bank profits. The study results consider the existence of two projects: one without the introduction to EURO and one with the introduction to EURO. We proceed through an incremental method to determine when profits will be produced. To further demonstrate this, we have calculated the NPV of the introduction to the EURO by considering the year 2002 as the basic year. The analysis shows that during the period 2002 - 2007 banks will face a loss in their bank profits. Further analysis indicates that profits will rapidly show increases in the long-term period. Therefore, the changeover to the EURO will probably be very lucrative for the banking system of Greece and the economy in general over the long-term.

Detecting falsified financial statements: a comparative study using multicriteria analysis and multivariate statistical techniques

Falsifying financial statements involves the manipulation of financial accounts by overstating assets, sales and profit, or understating liabilities, expenses or losses. This paper explores the effectiveness of an innovative classification methodology in detecting firms that issue falsified financial statements (FFS) and the identification of the factors associated to FFS. The methodology is based on the concepts of multicriteria decision aid (MCDA) and the application of the UTADIS classification method (UTilites Additives DIScriminantes). A sample of 76 Greek firms (38 with FFS and 38 non-FFS) described over ten financial ratios is used for detecting factors associated with FFS. A jackknife procedure approach is employed for model validation and comparison with multivariate statistical techniques, namely discriminant and logit analysis. The results indicate that the proposed MCDA methodology outperforms traditional statistical techniques which are widely used for FFS detection purposes. Furthermore, the results indicate that the investigation of financial information can be helpful towards the identification of FFS and highlight the importance of financial ratios such as the total debt to total assets ratio, the inventories to sales ratio, the net profit to sales ratio and the sales to total assets ratio.